Deep Learning on the SaturnV Cluster

“Machine Learning is among the most important developments in the history of computing. Deep learning is one of the fastest growing areas of machine learning and a hot topic in both academia and industry. It has dramatically improved the state-of-the-art in areas such as speech recognition, computer vision, predicting the activity of drug molecules, and many other machine learning tasks. The basic idea of deep learning is to automatically learn to represent data in multiple layers of increasing abstraction, thus helping to discover intricate structure in large datasets. NVIDIA has invested in SaturnV, a large GPU-accelerated cluster, (#28 on the November 2016 Top500 list) to support internal machine learning projects. After an introduction to deep learning on GPUs, we will address a selection of open questions programmers and users may face when using deep learning for their work on these clusters.”

Gunter Roeth joined NVIDIA as a Solution Architect two years ago having previously worked at Cray, HP, Sun Microsystems and most recently BULL. He has a Master in geophysics from the Institut de Physique du Globe (IPG) in Paris and has completed a PhD in seismology on the use of neural networks (artificial intelligence) for interpreting geophysical data.

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